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作 者:唐振兴 钱语然 任芮葶 宋万忠[3] 李宇[1] Tang Zhenxing;Qian Yuran;Ren Ruiting;Song Wanzhong;Li Yu(State Key Laboratory of Oral Diseases&National Center for Stomatology&National Clinical Research Center for Oral Diseases&Dept.of Orthodontics,West China Hospital of Stomatology,Sichuan University,Chengdu 610041,China;Dept.of Stomatology,Chengdu Seventh People’s Hospital(Affiliated Cancer Hospital of Chengdu Medical College),Chengdu 610213,China;College of Computer Science,Sichuan University,Chengdu 610065,China)
机构地区:[1]口腔疾病防治全国重点实验室、国家口腔医学中心、国家口腔疾病临床医学研究中心、四川大学华西口腔医院正畸科,成都610041 [2]成都市第七人民医院(成都医学院附属肿瘤医院)口腔科,成都610213 [3]四川大学计算机学院,成都610065
出 处:《华西口腔医学杂志》2024年第3期334-339,共6页West China Journal of Stomatology
基 金:四川省重大科技专项项目(2022ZDZX0031);四川大学华西口腔医院探索与研发项目(交叉学科创新项目RD-03-20-2003)。
摘 要:目的拟建立一种将自主最大笑容(AMS)三维面像与数字化三维牙列模型整合的方法,以实现在三维面像背景下显示数字化正畸终末位设计的目的。方法利用Geomagic Studio软件,通过手动注册和全局注册功能,将AMS三维面像和初始牙列模型进行配准对齐,然后用终末位牙列模型在原位替换初始牙列模型,并去除AMS三维面像口内区域,从而实现AMS三维面像和终末位牙列模型的融合显示。计算AMS三维面像和初始牙列模型上4组对应标志点对间的距离,通过配对t检验评估配准操作的准确性。结果该方法成功实现了AMS三维面像与初始、终末三维牙列模型的整合。两次配准对齐后,点对间的平均距离分别为(1.19±0.55)mm和(1.55±0.59)mm。两次测量结果的差异无统计学意义(P>0.05),且具有很高的一致性(组内相关性系数=0.914)。结论本研究建立了AMS三维面像与数字化初始、终末三维牙列模型整合的方法。该方法具有较高的准确性,有助于实现在三维面像背景下数字化正畸终末位设计效果的显示,从而提升以隐形正畸为代表的数字化正畸终末位设计的质量。Objective This study aims to establish an approach to integrate autonomous maximal smile(AMS)3D facial image with digital 3D dental models to demonstrate the digital orthodontic set-up in the 3D facial context.Methods Using Geomagic Studio software,the AMS 3D facial image and pre-treatment dental model were manually and globally registered.Subsequently,the pretreatment dental model was substituted with the predicted post-treatment dental model.The intraoral region of the AMS 3D facial image was removed,achieving a conjunctive display of the AMS 3D facial image and the post-treatment dental set-up.The distances between four groups of corresponding landmark pairs on the AMS 3D facial image and the pre-treatment dental set-up were calculated,and the accuracy of the registration operation was evaluated by paired t-test.Results The novel approach effectively facilitated the integration of AMS 3D facial images with the pre-treatment and predicted post-treatment 3D dental models.The average distances between the pairs of points were(1.19±0.55)mm and(1.55±0.59)mm for the two registrations,respectively.Notably,no statistically significant difference was observed between the two measurements(P>0.05),indicating a high agreement(intraclass correlation coefficient=0.914).Conclu⁃sion This study established an approach to integrate AMS 3D facial images with digital 3D dental models.Through this approach,the digital orthodontic set-up design can be displayed in the context of a 3D facial image,which may help to improve the quality of outcome set-up in digital orthodontics,such as clear aligner therapy.
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